Maintaining a state of good repair with predictive analytics [Splunk Enterprise, Splunk Machine Learning Toolkit, AI/ML]

Take a deep dive in this enablement focused presentation where we cover the background, data and how to implement 3 Splunk solutions entirely captured in this sessions' companion app that shows how to use Splunk for maintaining a state of good repair, make data-driven decisions to garner rate payer confidence and proactively realize conservation goals.  The use cases covered in this session are: *** Corrosion Analytics - See how to use machine learning combined with ArcGIS, Maximo and Corrosion data to create an interactive map to predict pipe failures and replacement priorities based on proximity to sensitive infrastructure. *** Mobile Work Fleet - see how to use scripted inputs to develop asset management dashboards, make data driven purchasing decisions and optimize routes. *** Water Leak detection - see how Splunk's Machine Learning Toolkit can be used to easily detect anomalous consumption based on user behavior and automate alerting utilities and customers to prevent water waste.

Speaker(s)

Tony Nesavich, Staff Sales Engineer, Splunk

Slides PDF link - https://conf.splunk.com/files/2019/slides/IOT1318.pdf?podcast=1577146258